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  <head>
    <title>Garment choice parameters</title>
  </head>
  <body>
    
    <h1>Garment choice parameters</h1>

    <h3><a href="#introduction">1 Introduction</a></h3>
    <h3><a href="#parameters">2 Parameters</a></h3>
    <h3><a href="#evaluation">3 How parameters are evaluated</a></h3>
    <h3><a href="#table_of_values">4 Table of values</a></h3>

    <h3><a name="introduction">1 Introduction</a></h3>
    <p>
      This page shows the list of the parameters computed for the garment
      choice.  Every parameter contributes to provide a score to the garment,
      the garment with highest score is proposed in the selection.
    </p>
    <h3><a name="parameters">2 Parameters</a></h3>
    <p>
      The meanings and values of the paramters are explained below:
      <h5>2.1 Preference</h5>
      It's computed according to the grade assigned to the garment.
      <h5>2.2 Date of purchase</h5>
      The newer is the garment, the higher score it gets.
      <h5>2.3 Last selection</h5>
      If the garment was recently selected it gets a low score.
      <h5>2.4 Selection count</h5>
      It depends on how many times the garment was selected in the last 30
      days. If it was selected often it gets a low score.
      <h5>2.5 Random</h5>
      A random value to let the coiche be not deterministic.
    </p>
    <h3><a name="evaluation">3 How parameters are evaluated</a></h3>
    <p>
      Every parameter has an absolute value and a weighted one; the first is
      computed referring to the constraints explained above, the second is
      taken from the first, multiplied by a certain coefficient according to the
      importance of the parameter in the overall count.
    </p>
    <p>
      Every parameter must be contained within a range stated by its maximum a
      minimun values.
    </p>
    <p>
      The coefficient used to get the weighed value can be proportional or
      logarithmic; in the first case there will be no relative difference with 
      the absolute value of the parameter, in the second case the computed
      value will be more-than-proportionally higher or lower in relation to the
      absolute value itself.
    </p>
    <p>
      The parameter can also be positive or negative, note that in case of
      logarithmic negative parameters the porportional relation explained above
      is inverted.
    </p>
    <h3><a name="table_of_values">4 Table of values</a></h3>
    <p>
      This is the summary table of parameter properties:
    </p>
    <p>
      <table border="1">
        <tr>
	  <td>
	    Parameter
	  </td>
	  <td>
	    +/-
	  </td>
	  <td>
	    Maximum
	  </td>
	  <td>
	    Minimum
	  </td>
	  <td>
	    Weight
	  </td>
	  <td>
	    Proportionality
	  </td>
        </tr>
        <tr>
	  <td>
	    <b>Preference</b>
	  </td>
	  <td>
	    Positive
	  </td>
	  <td>
	    0
	  </td>
	  <td>
	    10
	  </td>
	  <td>
	    1 1/2
	  </td>
	  <td>
	    Logarithmic
	  </td>
        </tr>
        <tr>
	  <td>
	    <b>Date of purchase</b>
	  </td>
	  <td>
	    Negative
	  </td>
	  <td>
	    0
	  </td>
	  <td>
	    12
	  </td>
	  <td>
	    1/4
	  </td>
	  <td>
	    Logarithmic
	  </td>
        </tr>
        <tr>
	  <td>
	    <b>Last selection</b>
	  </td>
	  <td>
	    Positive
	  </td>
	  <td>
	    0
	  </td>
	  <td>
	    30
	  </td>
	  <td>
	    1 1/2
	  </td>
	  <td>
	    Logarithmic
	  </td>
        </tr>
        <tr>
	  <td>
	    <b>Selection count</b>
	  </td>
	  <td>
	    Negative
	  </td>
	  <td>
	    0
	  </td>
	  <td>
	    30
	  </td>
	  <td>
	    2
	  </td>
	  <td>
	    Proportional
	  </td>
        </tr>
        <tr>
	  <td>
	    <b>Random</b>
	  </td>
	  <td>
	    Positive
	  </td>
	  <td>
	    0
	  </td>
	  <td>
	    100
	  </td>
	  <td>
	    1/2
	  </td>
	  <td>
	    Proportional
	  </td>
        </tr>
      </table>
    </p>
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